Multi-Source Data Fusion for Space Situational Awareness


To date, satellite tracking has been focused on validation of an object’s orbit and whether it is operational or not. While physics-based information, and thus accuracy of a space object’s track, is increasing—so too is the overall scale of objects to track. The space catalog is currently at 20K objects with expectations to increase to 100K and possibly 500K within 5 to 7 years. Given the increase in scale of objects expected and existence of congestion and deconfliction of orbits, maintaining the chain of custody from launch, validation of intent, attribution, and resolution of anomalies or actions have become of paramount importance to space operators. The ability to not just predict and avoid physical conjunctions with better fidelity, but the ability to assess an object’s risks before it gets into trouble may now be required.

In this project we are developing a modular evolving knowledge graph, called SpaceAware, for current and future space operations. SpaceAware addresses the current multi-data fusion challenge from information sources as disparate as orbitology, satellite updates, and socio-economic sources, while providing expansion capability for addressing space traffic management for commercial and operational missions. Through high-performance computing, plug-in algorithmic portals, an evolving knowledge graph, and the ability to provide indications and warnings, SpaceAware offers a backbone for the development of systems allowing multiple levels of operators and the ability for long-term commercial planners to play out multiple COAs through an evolving operating picture.